Module _protocols_sasa_scores_

compute_avge_scores( (Pose)pose, (vector1_Real)residue_avge, (vector1_Real)residue_normsasa, (float)average_avge, (float)average_normsasa) -> None :
    Compute normalize scores for the given pose based on average energies (hence "avgE") for pdb structures.
    Currently only scores non-terminal, non-disulfide, protein residues.
    The "avge" score for a residue is the difference between its per-residue score and the expected per-residue
    score for that residue type, conditioned on the residue SASA with a 1.4A probe.
    Right now, the following scores are excluded from the avge sum since they are often very large in native structures:
       fa_rep, fa_dun, pro_close, omega
    as well as paa_pp for glycine, since it's just weird. Could consider refitting these
    The normsasa is just the difference between a residues SASA-1.4 and the average SASA-1.4 for that residue type
    Refitting app and python code will be checked in shortly.
    

    C++ signature :
        void compute_avge_scores(core::pose::Pose,utility::vector1<double, std::allocator<double> > {lvalue},utility::vector1<double, std::allocator<double> > {lvalue},double {lvalue},double {lvalue})

compute_residue_sasas_for_sasa_scores( (float)probe_radius, (Pose)pose, (vector1_Real)rsd_sasa) -> None :
    Compute residue sasa values for use in deriving and assigning sasapack-like scores
    

    C++ signature :
        void compute_residue_sasas_for_sasa_scores(double,core::pose::Pose,utility::vector1<double, std::allocator<double> > {lvalue})

compute_sasapack_scores( (Pose)pose, (vector1_Real)residue_sasapack, (vector1_Real)residue_normsasa, (float)average_sasapack, (float)average_normsasa) -> None :
    Compute sasapack scores for the given pose.
    Currently only scores non-terminal, non-disulfide, protein residues.
    The sasapack score for a residue is the difference between its SASA with a 0.5A probe
    and the average SASA value for that residue-type in a large set of pdb structures, conditioned
    on the SASA with a 1.4A probe.
    The normsasa is just the difference between a residues SASA-1.4 and the average SASA-1.4 for that residue type
    Refitting app and python code will be checked in shortly.
    

    C++ signature :
        void compute_sasapack_scores(core::pose::Pose,utility::vector1<double, std::allocator<double> > {lvalue},utility::vector1<double, std::allocator<double> > {lvalue},double {lvalue},double {lvalue})